By way of brief background, cognitive radio is a paradigm for wireless communication in which either a network or a wireless node changes its transmission or reception parameters to communicate efficiently without interfering with licensed users. This alteration of parameters is based on actively monitoring several factors in the external and internal radio environment, such as radio frequency spectrum, user behavior and network state.
In cognitive radio systems, the unlicensed (secondary) users can use the licensed spectrum as long as the licensed (primary) user is absent at some particular time slot and some specific geographic location. However, when the primary user reappears (i.e., comes back and is present again), ideally, the secondary users should vacate the spectrum instantly to avoid interference with the primary user.
The explosive growth in wireless services over the past several years illustrates the huge and growing demand of the business community, consumers and the government for wireless communications. With this growth of communication applications, the spectrum has become even more congested. Even though the Federal Communications Commission (FCC) has expanded some spectral bands, these frequency bands are exclusively assigned to specific users or service providers. Such expansion does not necessarily guarantee that the bands are being used most efficiently all the time.
In this regard, it has been shown that most of the radio frequency spectrum is vastly under-utilized. For example, cellular network bands are overloaded in most parts of the world, but amateur radio or paging frequencies are not. Moreover, those rarely used frequency bands are assigned to specific services that cannot be accessed by unlicensed users, even where transmissions of the unlicensed users will not introduce any interference to the licensed service.
To deal with the conflicts between spectrum congestion and spectrum under-utilization, cognitive radio has been recently proposed as a smart and agile technology, which allows non-legitimate users to utilize licensed bands opportunistically. By detecting particular spectrum “holes” and jumping into them rapidly to meet demand for spectrum, cognitive radio can improve the spectrum utilization significantly. To guarantee a high spectrum efficiency while avoiding interference to licensed users, cognitive radio should be able to adapt to spectrum conditions flexibly. Hence, improvements for cognitive radio are desired in the areas of spectrum sensing, dynamic frequency selection and transmit power control.
One of the most challenging problems of cognitive radio is the interference that occurs when a cognitive radio accesses a licensed band, but fails to notice the presence of the licensed user. To address this problem, cognitive radios should be designed to co-exist with the licensed user without creating harmful interference. Some conventional techniques that have been proposed to mitigate interference by the unlicensed user in cognitive radio systems include: (1) an orthogonal frequency division multiplexing (OFDM) approach proposed to avoid the interference by leaving a set of subchannels unused, (2) a transform domain communication system (TDCS) approach proposed to mitigate the interference by not placing the waveform energy at corrupted spectral locations and (3) a power control approach proposed to allow cognitive radios to adjust their transmit powers in order to guarantee quality of service (QoS) to the primary system based on a measurement of local signal to noise ratio (SNR) of the primary signal.
To avoid interference to licensed users, however, the transmit power of cognitive radios should be limited based on the locations of the licensed users. The third approach above begins from the assumption that cognitive radios have no way of knowing these locations of the licensed users, and then proposes the use of SNR as a proxy measurement, however, if the primary receiver is a TV antenna on a roof, it might measure a SNR of 0 dB at one location, while a cognitive radio on the ground at the same location might measure −10 dB, and thus SNR is a weak proxy that does not appear to directly correlate to the locations of the licensed users.
In this regard, it is difficult to locate the licensed users for the cognitive radio in practice because the channels between the cognitive radio and the licensed users are usually unknown. Furthermore, the environment where the system is in operation may have a large delay spread and, hence, the channel model between cognitive radios and primary users is complicated by fading, shadowing and path loss effects.
In another conventional system, a local oscillator (LO) leakage power is exploited to try to locate the primary receivers. However, such an approach is difficult to apply in practice because the approach requires a sensor node mounted close to the primary receivers to detect the LO leakage power, which is not very practical.
Accordingly, improved systems and methods are desired for improving power control for cognitive radio systems that do not depend upon additional structure, such as sensor nodes for detecting LO leakage power, being added close to the primary receivers. Moreover, systems are desired that control power of a cognitive radio based on a measurement, related to distance to licensed users, which is not inherently flawed as with the third approach discussed above.
The above-described deficiencies of current designs are merely intended to provide an overview of some of the problems of today's designs, and are not intended to be exhaustive. Other problems with the state of the art of cognitive radio and corresponding benefits of the invention may become further apparent upon review of the following description of various non-limiting embodiments of the invention.